Organ and lesion detection.
The detection of organ and lesion is inspired by the object detection framework for natural images (e.g., Faster-RCNN [1]}, FPN [2]}, and Yolo [3]}). Besides, 3D spatial information of the medical data is explored in the 3D detection framework. In [4]}, a 3D-CNN classification approach was proposed to classify lung nodule candidates that were previously detected by the Faster-RCNN detector. The RPN [1]} was extended in [6]} to become 3D-RPN for 3D proposal generation to detect lung nodules. Different from the 3D detection framework, a multi-scale booster was proposed in [7]} with channel and spatial attentions that were integrated into FPN for suspicious lesion detection in 2D CT slices. The detection methods based on 2D image input reduced heavy computational cost brought in the 3D inputs for 3D detection methods.
